Rigorous exploration in a model-centric science via epistemic iteration
Open accessAbstract
Urgent attention is needed to address generalizability problems in psychology. However, the current dominant paradigm centered on dichotomous results and rapid discoveries cannot provide the solution because of its theoretical inadequacies. We propose a paradigm shift towards a model-centric science, which provides the sophistication to understanding the sources of generalizability and promote systematic exploration. In a model-centric paradigm, scientific activity involves iteratively building and refining theoretical, empirical, and statistical models that communicate with each other. This approach is transparent, and efficient in addressing generalizability issues. We illustrate the nature of scientific activity in a model-centric system and its potential for advancing the field of psychology.
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This generally involves translating a set of theoretical propositions or principles into a formal process theory that in turn generates predictions about target phenomena that may be subjected to empirical validation.
“This generally involves translating a set of theoretical propositions or principles into a formal process theory that in turn generates predictions about target phenomena that may be subjected to empirical validation (Devezer & Buzbas, 2023; for a philosophical overview, see Vorms, 2018).”
From Integrated information and predictive processing theories of consciousness: An adversarial collaborative review (2026) · cites this paper as Devezer & Buzbas, 2023
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Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations
Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016) · European Journal of Epidemiology · doi:10.1007/s10654-016-0149-3 · Cited by 3,200 · see citing works
Constraints on Generality (COG): A Proposed Addition to All Empirical Papers
Simons, D. J., Shoda, Y., & Lindsay, D. S. (2017) · Perspectives on Psychological Science · doi:10.1177/1745691617708630 · Cited by 986 · see citing works
WHY SUMMARIES OF RESEARCH ON PSYCHOLOGICAL THEORIES ARE OFTEN UNINTERPRETABLE
Meehl, P. E. (1990) · Psychological Reports · doi:10.2466/pr0.1990.66.1.195 · Cited by 901 · see citing works
YOU CAN'T PLAY 20 QUESTIONS WITH NATURE AND WIN: PROJECTIVE COMMENTS ON THE PAPERS OF THIS SYMPOSIUM
Newell, A. (1973) · Visual Information Processing · doi:10.1016/b978-0-12-170150-5.50012-3 · Cited by 820 · see citing works
Yarkoni, T. (2022) · Behavioral and Brain Sciences · doi:10.1017/s0140525x20001685 · Cited by 701 · see citing works
The strategy of model-based science
Godfrey‐Smith, P. (2006) · Biology & Philosophy · doi:10.1007/s10539-006-9054-6 · Cited by 549 · see citing works
van Rooij, I., & Baggio, G. (2021) · Perspectives on Psychological Science · doi:10.1177/1745691620970604 · Cited by 354 · see citing works
Statistical Rituals: The Replication Delusion and How We Got There
Gigerenzer, G. (2018) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245918771329 · Cited by 263 · see citing works
Toward a principled Bayesian workflow in cognitive science.
Schad, D. J., Betancourt, M., & Vasishth, S. (2021) · Psychological Methods · doi:10.1037/met0000275 · Cited by 252 · see citing works
Drawing an elephant with four complex parameters
Mayer, J. M., Khairy, K. A., & Howard, J. (2010) · American Journal of Physics · doi:10.1119/1.3254017 · Cited by 192 · see citing works
Devezer, B., Nardin, L. G., Baumgaertner, B. O., & Buzbas, E. O. (2019) · PLoS ONE · doi:10.1371/journal.pone.0216125 · Cited by 107 · see citing works
Self-citationPotochnik, A. (2015) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2015.05.008 · Cited by 81 · see citing works
Why I am not a scientist: anthropology and modern knowledge
(2009) · Choice Reviews Online · doi:10.5860/choice.47-1376 · Cited by 57 · see citing works
Kennedy, L., & Gelman, A. (2021) · Psychological Methods · doi:10.1037/met0000362 · Cited by 53 · see citing works
Psychological models and their distractors
van Rooij, I. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-022-00031-5 · Cited by 30 · see citing works
Generalizations: The grail and the gremlins.
Bauer, P. J. (2023) · Journal of Applied Research in Memory and Cognition · doi:10.1037/mac0000106 · Cited by 24 · see citing works
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Costello, T. H., Newton, C., Lin, H., & Pennycook, G. (2023) · doi:10.31234/osf.io/gux95 · Cited by 17 · see citing works
Zgonnikov, A., Beckers, N., George, A., Abbink, D. A., & Jonker, C. (2024) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2024.103224 · Cited by 14 · see citing works
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Bauer, P. J. (2023) · Journal of Applied Research in Memory and Cognition · doi:10.1037/mac0000125 · Cited by 5 · see citing works
Zgonnikov, A., Beckers, N., George, A., Abbink, D. A., & Jonker, C. M. (2023) · doi:10.31234/osf.io/3cu8b · Cited by 5 · see citing works
Lemaitre, J. C., Popelka, D., Ribotta, B., Westlake, H. E., Chakrabarti, S., Li, X., Hanson, M. A., Jiang, H., Cara, F. D., Kurant, E., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.07.663460 · Cited by 5 · see citing works
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Cao, A., Lewis, M. L., Tsuji, S., Bergmann, C., Cristià, A., & Frank, M. C. (2025) · Developmental Science · doi:10.1111/desc.70028 · Cited by 3 · see citing works
Lemaitre, J. C., Popelka, D., Ribotta, B., Westlake, H. E., Chakrabarti, S., Xiaoxue, L., Hanson, M. A., Jiang, H., Cara, F. D., Kurant, E., et al. (2026) · eLife · doi:10.7554/elife.108403.1 · Cited by 3 · see citing works
Corcoran, A. W., Haun, A. M., Dorman, R., Tononi, G., Friston, K. J., & Pennartz, C. M. A. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106742 · Cited by 2 · see citing works
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Buzbas, E. O., & Devezer, B. (2024) · Entropy · doi:10.3390/e26100842
Self-citationFostering transparency and reproducibility in psychological science.
Lindsay, D. S. (2025) · Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · doi:10.1037/cep0000381
Advanced Data Analysis in Quantitative Research
Almusaed, A., Almssad, A., & Yitmen, İ. (2025) · Springer eBooks · doi:10.1007/978-3-031-97393-2_19
Lemaitre, J. C., Popelka, D., Ribotta, B., Westlake, H. E., Chakrabarti, S., Xiaoxue, L., Hanson, M. A., Jiang, H., Cara, F. D., Kurant, E., et al. (2026) · eLife · doi:10.7554/elife.108403
Lemaitre, J. C., Popelka, D., Ribotta, B., Westlake, H. E., Chakrabarti, S., Xiaoxue, L., Hanson, M. A., Jiang, H., Cara, F. D., Kurant, E., et al. (2026) · eLife · doi:10.7554/elife.108403.2
- Authors
- Devezer, B., & Buzbas, E. O.
- Affiliations
- University of Idaho (US)
- Venue
- Journal of Applied Research in Memory and Cognition
- Published
- 2023-06
- Volume
- 12
- Issue
- 2
- Pages
- 189-194
- ISSN
- 2211-3681 (ISSN-L)
- 2211-369X
- PMC
- PMC10888142
- OpenAlex
- W4383372597
- Cited by
- 27
- References
- 18
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 8 · 2023: 4
- FWCI
- 32.39
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Applied Research in Memory and Cognition (publishedVersion, other-oa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- MetArXiv (OSF Preprints) (submittedVersion, cc-by-nd)
- MetArXiv (OSF Preprints) (submittedVersion)
- Funders
- National Institute of General Medical Sciences (P20GM104420)
- Topics
- Social Sciences › Psychology › General Psychology › Academic and Historical Perspectives in Psychology
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- generalizability, paradigm shift, theoretical model, statistical models, empirical model, scientific research, psychological research methods
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